Bioluminescence refers to the production of ecologically functional light by living organisms. It is widespread in the marine environment, where it occurs in a broad range of phyla. The deep pelagic ocean is the largest biome on earth and is chronically under-sampled. Underwater camera systems offer a rapid sampling method for this zone. In the current study, the ICDeep (Image Intensied Charge Coupled Device for Deep-sea research) profiler was used to record digital video of bioluminescent organisms through the deep water column. This work proposes a new automatic detection and counting methods for bioluminescent organisms represented as ashes within video data acquired through the camera based on computer vision algorithms. The proposed method has been validated by a ground truthed sequence of bioluminescent events resulting in a high correct detection rate and real time processing execution.

Automated video imaging system for counting deep-sea bioluminescence organisms events

Mazzei Luca;Marini Simone;
2014

Abstract

Bioluminescence refers to the production of ecologically functional light by living organisms. It is widespread in the marine environment, where it occurs in a broad range of phyla. The deep pelagic ocean is the largest biome on earth and is chronically under-sampled. Underwater camera systems offer a rapid sampling method for this zone. In the current study, the ICDeep (Image Intensied Charge Coupled Device for Deep-sea research) profiler was used to record digital video of bioluminescent organisms through the deep water column. This work proposes a new automatic detection and counting methods for bioluminescent organisms represented as ashes within video data acquired through the camera based on computer vision algorithms. The proposed method has been validated by a ground truthed sequence of bioluminescent events resulting in a high correct detection rate and real time processing execution.
2014
Istituto di Scienze Marine - ISMAR
9781479967131
bioluminescent organisms
deep sea
under- water computer vision
underwater object recognition.
video tracking
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/232219
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